An annotated ventricular tachycardia (VT) alarm database: Toward a uniform standard for optimizing automated VT identification in hospitalized patients.

BACKGROUND: False ventricular tachycardia (VT) alarms are common during in-hospital electrocardiographic (ECG) monitoring. Prior research shows that the majority of false VT can be attributed to algorithm deficiencies. PURPOSE: The purpose of this study was: (1) to describe the creation of a VT database annotated by ECG experts and (2) to determine true vs. false VT using a new VT algorithm created by our group. METHODS: The VT algorithm was processed in 5320 consecutive ICU patients with 572,574 h of ECG and physiologic monitoring. A search algorithm identified potential VT, defined as: heart rate >100 beats/min, QRSs > 120 ms, and change in QRS morphology in >6 consecutive beats compared to the preceding native rhythm. Seven ECG channels, SpO2 , and arterial blood pressure waveforms were processed and loaded into a web-based annotation software program. Five PhD-prepared nurse scientists performed the annotations. RESULTS: Of the 5320 ICU patients, 858 (16.13%) had 22,325 VTs. After three levels of iterative annotations, a total of 11,970 (53.62%) were adjudicated as true, 6485 (29.05%) as false, and 3870 (17.33%) were unresolved. The unresolved VTs were concentrated in 17 patients (1.98%). Of the 3870 unresolved VTs, 85.7% (n = 3281) were confounded by ventricular paced rhythm, 10.8% (n = 414) by underlying BBB, and 3.5% (n = 133) had a combination of both. CONCLUSIONS: The database described here represents the single largest human-annotated database to date. The database includes consecutive ICU patients, with true, false, and challenging VTs (unresolved) and could serve as a gold standard database to develop and test new VT algorithms.

Ischemic Pre-Conditioning is Present in Patients with Non-ST Elevation Myocardial Infarction and ECG Derived Moderate Obstructive Sleep Apnea.

Background: Obstructive Sleep Apnea (OSA) is associated with an increased risk of cardiovascular events, including Acute Coronary Syndrome (ACS). There is conflicting evidence that suggests OSA has a cardioprotective effect (i.e., lower troponin), via ischemic pre-conditioning, in patients with ACS. Purpose: This study had two aims: (1) compare peak troponin between non-ST elevation (NSTE) ACS patients with and without moderate OSA identified using a Holter derived respiratory disturbance index (HDRDI); and (2) determine the frequency of transient myocardial ischemia (TMI) between NSTE-ACS patients with and without moderate HDRDI. Method: This was a secondary analysis. OSA events were identified from 12-lead ECG Holter recordings using QRSs, R-R intervals, and the myogram. Moderate OSA was defined as an HDRDI ≥15 events per/hour. TMI was defined as ≥1 millimeter of ST-segment ↑ or ↓, in ≥ 1 ECG lead, ≥ 1 minute. Results: In 110 NSTE-ACS patients, 39% (n=43) had moderate HDRDI. Peak troponin was higher in patients with moderate HDRDI (6.8 ng/ml yes vs. 10.2 ng/ml no; p=0.037). There was a trend for fewer TMI events, but there were no differences (16% yes vs. 30% no; p=0.081). Conclusions: NSTE-ACS patients with moderate HDRDI have less cardiac injury than those without moderate HDRDI measured using a novel ECG derived method. These findings corroborate prior studies suggesting a possible cardioprotective effect of OSA in ACS patients via ischemic pre-condition. There was a trend for fewer TMI events in moderate HDRDI patients, but there was no statistical difference. Future research should explore the underlying physiologic mechanisms of this finding.

Agreement of Computerized QT and QTc Interval Measurements Between Both Bedside and Expert Nurses Using Electronic Calipers.

BACKGROUND: In hospitalized patients, QT/QTc (heart rate corrected) prolongation on the electrocardiogram (ECG) increases the risk of torsade de pointes. Manual measurements are time-consuming and often inaccurate. Some bedside monitors automatically and continuously measure QT/QTc; however, the agreement between computerized versus nurse-measured values has not been evaluated. OBJECTIVE: The aim of this study was to examine the agreement between computerized QT/QTc and bedside and expert nurses who used electronic calipers. METHODS: This was a prospective observational study in 3 intensive care units. Up to 2 QT/QTc measurements (milliseconds) per patient were collected. Bland-Altman test was used to analyze measurement agreement. RESULTS: A total of 54 QT/QTc measurements from 34 patients admitted to the ICU were included. The mean difference (bias) for QT comparisons was as follows: computerized versus expert nurses, -11.04 ± 4.45 milliseconds (95% confidence interval [CI], -2.3 to -19.8; P = .016), and computerized versus bedside nurses, -13.72 ± 6.70 (95% CI, -0.70 to -26.8; P = .044). The mean bias for QTc comparisons was as follows: computerized versus expert nurses, -12.46 ± 5.80 (95% CI, -1.1 to -23.8; P = .035), and computerized versus bedside nurses, -18.49 ± 7.90 (95% CI, -3.0 to -33.9; P = .022). CONCLUSION: Computerized QT/QTc measurements calculated by bedside monitor software and measurements performed by nurses were in close agreement; statistically significant differences were found, but differences were less than 20 milliseconds (on-half of a small box), indicating no clinical significance. Computerized measurements may be a suitable alternative to nurse-measured QT/QTc. This could reduce inaccuracies and nurse burden while increasing adherence to practice recommendations. Further research comparing computerized QT/QTc from bedside monitoring to standard 12-lead electrocardiogram in a larger sample, including non-ICU patients, is needed.

Evaluation of premature ventricular complexes during in-hospital ECG monitoring as a predictor of ventricular tachycardia in an intensive care unit cohort.

In-hospital electrocardiographic (ECG) monitors are typically configured to alarm for premature ventricular complexes (PVCs) due to the potential association of PVCs with ventricular tachycardia (VT). However, no contemporary hospital-based studies have examined the association of PVCs with VT. Hence, the benefit of PVC monitoring in hospitalized patients is largely unknown. This secondary analysis used a large PVC alarm data set to determine whether PVCs identified during continuous ECG monitoring were associated with VT, in-hospital cardiac arrest (IHCA), and/or death in a cohort of adult intensive care unit patients. Six PVC types were examined (i.e., isolated, bigeminy, trigeminy, couplets, R-on-T, and run PVCs) and were compared between patients with and without VT, IHCA, and/or death. Of 445 patients, 48 (10.8%) had VT; 11 (2.5%) had IHCA; and 49 (11%) died. Isolated and run PVC counts were higher in the VT group (p = 0.03 both), but group differences were not seen for the other four PVC types. The regression models showed no significant associations between any of the six PVC types and VT or death, although confidence intervals were wide. Due to the small number of cases, we were unable to test for associations between PVCs and IHCA. Our findings suggest that we should question the clinical relevance of activating PVC alarms as a forewarning of VT, and more work should be done with larger sample sizes. A more precise characterization of clinically relevant PVCs that might be associated with VT is warranted.

Premature ventricular complexes during continuous electrocardiographic monitoring in the intensive care unit: Occurrence rates and associated patient characteristics.

AIMS AND OBJECTIVES: This study examined the occurrence rate of specific types of premature ventricular complex (PVC) alarms and whether patient demographic and/or clinical characteristics were associated with PVC occurrences. BACKGROUND: Because PVCs can signal myocardial irritability, in-hospital electrocardiographic (ECG) monitors are typically configured to alert nurses when they occur. However, PVC alarms are common and can contribute to alarm fatigue. A better understanding of occurrences of PVCs could help guide alarm management strategies. DESIGN: A secondary quantitative analysis from an alarm study. METHODS: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was followed. Seven PVC alarm types (vendor-specific) were described, and included isolated, couplet, bigeminy, trigeminy, run PVC (i.e. VT >2), R-on-T and PVCs/min. Negative binomial and hurdle regression analyses were computed to examine the association of patient demographic and clinical characteristics with each PVC type. RESULTS: A total of 797,072 PVC alarms (45,271 monitoring hours) occurred in 446 patients, including six who had disproportionately high PVC alarm counts (40% of the total alarms). Isolated PVCs were the most frequent type (81.13%) while R-on-T were the least common (0.29%). Significant predictors associated with higher alarms rates: older age (isolated PVCs, bigeminy and couplets); male sex and presence of PVCs on the 12-lead ECG (isolated PVCs). Hyperkalaemia at ICU admission was associated with a lower R-on-T type PVCs. CONCLUSIONS: Only a few distinct demographic and clinical characteristics were associated with the occurrence rate of PVC alarms. Further research is warranted to examine whether PVCs were associated with adverse outcomes, which could guide alarm management strategies to reduce unnecessary PVC alarms. RELEVANCE TO CLINICAL PRACTICE: Targeted alarm strategies, such as turning off certain PVC-type alarms and evaluating alarm trends in the first 24 h of admission in select patients, might add to the current practice of alarm management.

Agreement between respiratory rate measurement using a combined electrocardiographic derived method versus impedance from pneumography.

BACKGROUND: Impedance pneumography (IP) is the current device-driven method used to measure respiratory rate (RR) in hospitalized patients. However, RR alarms are common and contribute to alarm fatigue. While RR derived from electrocardiographic (ECG) waveforms hold promise, they have not been compared to the IP method. PURPOSE: Study examined the agreement between the IP and combined-ECG derived (EDR) for normal RR (≥12 or ≤20 breaths/minute [bpm]); low RR (≤5 bpm); and high RR (≥30 bpm). METHODOLOGY: One-hundred intensive care unit patients were included by RR group: (1) normal RR (n = 50; 25 low RR and 25 high RR); (2) low RR (n = 50); and (3) high RR (n = 50). Bland-Altman analysis was used to evaluate agreement. RESULTS: For normal RR, a significant bias difference of -1.00 + 2.11 (95% CI -1.60 to -0.40) and 95% limit of agreement (LOA) of -5.13 to 3.13 was found. For low RR, a significant bias difference of -16.54 + 6.02 (95% CI: -18.25 to -14.83) and a 95% LOA of -28.33 to - 4.75 was found. For high RR, a significant bias difference of 17.94 + 12.01 (95% CI: 14.53 to 21.35) and 95% LOA of -5.60 to 41.48 was found. CONCLUSION: Combined-EDR method had good agreement with the IP method for normal RR. However, for the low RR, combined-EDR was consistently higher than the IP method and almost always lower for the high RR, which could reduce the number of RR alarms. However, replication in a larger sample including confirmation with visual assessment is warranted.

A review of the literature on the accuracy, strengths, and limitations of visual, thoracic impedance, and electrocardiographic methods used to measure respiratory rate in hospitalized patients.

BACKGROUND: Respiratory rate (RR) is one of the most important indicators of a patient's health. In critically ill patients, unrecognized changes in RR are associated with poorer outcomes. Visual assessment (VA), impedance pneumography (IP), and electrocardiographic-derived respiration (EDR) are the three most commonly used methods to assess RR. While VA and IP are widely used in hospitals, the EDR method has not been validated for use in hospitalized patients. Additionally, little is known about their accuracy compared with one another. The purpose of this systematic review was to compare the accuracy, strengths, and limitations of VA of RR to two methods that use physiologic data, namely IP and EDR. METHODS: A systematic review of the literature was undertaken using prespecified inclusion and exclusion criteria. Each of the studies was evaluated using standardized criteria. RESULTS: Full manuscripts for 23 studies were reviewed, and four studies were included in this review. Three studies compared VA to IP and one study compared VA to EDR. In terms of accuracy, when Bland-Altman analyses were performed, the upper and lower levels of agreement were extremely poor for both the VA and IP and VA and EDR comparisons. CONCLUSION: Given the paucity of research and the fact that no studies have compared all three methods, no definitive conclusions can be drawn about the accuracy of these three methods. The clinical importance of accurate assessment of RR warrants new research with rigorous designs to determine the accuracy, and clinically meaningful levels of agreement of these methods.

Prehospital ECG with ST-depression and T-wave inversion are associated with new onset heart failure in individuals transported by ambulance for suspected acute coronary syndrome.

BACKGROUND: Prehospital electrocardiogram(s) (ECG) can improve early detection of acute coronary syndrome (ST-segment elevation myocardial infarction [STEMI], non-STEMI, and unstable angina) and inform prehospital activation of cardiac catheterization lab; thus, reducing total ischemic time and improving patient outcomes. Less is known, however, about the association of prehospital ECG ischemic findings and long term adverse clinical events. With this in mind, this study was designed to examine the: 1) frequency of prehospital ECGs for acute myocardial ischemia (ST-elevation, ST-depression, and/or T-wave inversion); and, 2) whether any of these specific ECG features are associated with adverse clinical events within 30 day of initial presentation to the emergency department (ED). METHODS: We included consecutive patients ≥ 21 years during a five-year period (2013-2017), who were transported by ambulance to the ED with non-traumatic chest pain and/or anginal equivalent(s) and had a prehospital 12­lead ECG. Two cardiologists (LG, EC), blinded to clinical data, interpreted the 12­lead ECGs applying current guideline based ischemia criteria. Adverse clinical events, return to ED, and rehospitalization evaluated at 30-days. RESULTS: We identified 3646 patients (mean age, 59.7 years ±15.7; 45% female) with ECGs, of which N = 3587 had data on the three ischemic markers of interest. Of these, 1762 (49.1%) had ECG evidence of ischemia. In adjusted logistic regression models, those with T-wave inversion had a higher odds (OR = 1.59) of new onset heart failure, while ST-elevation was associated with lower odds (OR = 0.69). Patients with ST-depression had higher odds of new onset heart failure and death within 30 days (OR = 1.29, 1.49 respectively), but this association attenuated after controlling for other ECG features. CONCLUSIONS: ST-depression and/or T-wave inversion are independent predictors of new onset heart failure, within 30 days of initial ED presentation. Our study in a large cohort of patients, suggests that using ECG ST-elevation alone may not capture patients with ischemia who may benefit from aggressive anti-ischemic therapies to reduce myocardial damage with resultant heart failure.

A Statewide Assessment of Prehospital Electrocardiography Approaches of Acquisition and Interpretation for ST-Elevation Myocardial Infarction Based on Emergency Medical Services Characteristics.

Background: The American Heart Association recommends acquiring and interpreting prehospital electrocardiograms (ECG) for patients transported by Emergency Medical Services (EMS) to the emergency department with symptoms highly suspicious of acute coronary syndrome. If interpreted correctly, prehospital ECGs have the potential to improve early detection of ST-elevation myocardial infarction (STEMI) and inform prehospital activation of the cardiac catheterization laboratory, thus reducing total ischemic time and improving patient outcomes. Standardized protocols for prehospital ECG interpretation methods are lacking due to variations in EMS system design, training, and procedures. Objectives: We aimed to describe approaches for prehospital ECG interpretation in EMS systems across North Carolina (NC), and examine potential differences among systems. Methods: A 35-item internet survey was sent to all NC EMS systems (n = 99). Questions pertaining to prehospital ECG interpretation methods included: paramedic, computerized algorithm (i.e., software interpretation), combined approaches, and/or transmission for physician interpretation, transmission capability, cardiac catheterization laboratory activation, and EMS system characteristics (e.g. rural versus urban). Data were summarized and compared. Results: A total of 96 EMS systems across NC responded to the survey (97% response rate); of these, 69% were rural. EMS medical directors (53%) or EMS administrative directors (42%) completed the majority of surveys. While 91% of EMS systems had a prehospital ECG interpretation protocol in place, only 61% had a written cardiac catheterization laboratory activation policy. More than half (55%) of systems reported paramedic interpretation of prehospital ECGs, followed by a combined paramedic and software interpretation approach (39%), physician interpretation (4%), or software interpretation only approach (2%). Nearly 80% of EMS systems transmitted prehospital ECGs to receiving hospitals (always or sometimes), regardless of interpretation method. All EMS systems had some paid versus non-paid EMS personnel and the majority (86%) had both basic and advanced life support capabilities. Conclusions: Most NC EMS systems had a paramedic only ECG interpretation or paramedic in combination with a computerized algorithm approach. Very few used a physician read approach following transmission, even in rural service areas.

Technological Distractions (Part 2): A Summary of Approaches to Manage Clinical Alarms With Intent to Reduce Alarm Fatigue.

OBJECTIVE: Alarm fatigue is a widely recognized safety and quality problem where exposure to high rates of clinical alarms results in desensitization leading to dismissal of or slowed response to alarms. Nonactionable alarms are thought to be especially problematic. Despite these concerns, the number of clinical alarm signals has been increasing as an everincreasing number of medical technologies are added to the clinical care environment. DATA SOURCES: PubMed, SCOPUS, Embase, and CINAHL. STUDY SELECTION: We performed a systematic review of the literature focused on clinical alarms. We asked a primary key question; "what interventions have been attempted and resulted in the success of reducing alarm fatigue?" and 3-secondary key questions; "what are the negative effects on patients/families; what are the balancing outcomes (unintended consequences of interventions); and what human factor approaches apply to making an effective alarm?" DATA EXTRACTION: Articles relevant to the Key Questions were selected through an iterative review process and relevant data was extracted using a standardized tool. DATA SYNTHESIS: We found 62 articles that had relevant and usable data for at least one key question. We found that no study used/developed a clear definition of "alarm fatigue." For our primary key question 1, the relevant studies focused on three main areas: quality improvement/bundled activities; intervention comparisons; and analysis of algorithm-based false and total alarm suppression. All sought to reduce the number of total alarms and/or false alarms to improve the positive predictive value. Most studies were successful to varying degrees. None measured alarm fatigue directly. CONCLUSIONS: There is no agreed upon valid metric(s) for alarm fatigue, and the current methods are mostly indirect. Assuming that reducing the number of alarms and/or improving positive predictive value can reduce alarm fatigue, there are promising avenues to address patient safety and quality problem. Further investment is warranted not only in interventions that may reduce alarm fatigue but also in defining how to best measure it.

Wavelet leader multifractal analysis of heart rate variability in atrial fibrillation.

BACKGROUND: Accurate and timely detection of atrial fibrillation (AF) episodes is important in primarily and secondary prevention of ischemic stroke and heart-related problems. In this work, heart rate regularity of ECG inter-beat intervals was investigated in episodes of AF and other rhythms using a wavelet leader based multifractal analysis. Our aim was to improve the detectability of AF episodes. METHODS: Inter-beat intervals from 25 ECG recordings available in the MIT-BIH atrial fibrillation database were analysed. Four types of annotated rhythms (atrial fibrillation, atrial flutter, AV junctional rhythm, and other rhythms) were available. A wavelet leader based multifractal analysis was applied to 5 min non-overlapping windows of each recording to estimate the multifractal spectrum in each window. The width of the multifractal spectrum was analysed for its discrimination power between rhythm episodes. RESULTS: In 10 of 25 recordings, the width of multifractal spectrum was significantly lower in episodes of AF than in other rhythms indicating increased regularity during AF. High classification accuracy (95%) of AF episodes was achieved using a combination of features derived from the multifractal analysis and statistical central moment features. CONCLUSIONS: An increase in the regularity of inter-beat intervals was observed during AF episodes by means of multifractal analysis. Multifractal features may be used to improve AF detection accuracy.

Evaluation of ECG algorithms designed to improve detect of transient myocardial ischemia to minimize false alarms in patients with suspected acute coronary syndrome.

BACKGROUND: Patients hospitalized for suspected acute coronary syndrome (ACS) are at risk for transient myocardial ischemia. During the "rule-out" phase, continuous ECG ST-segment monitoring can identify transient myocardial ischemia, even when asymptomatic. However, current ST-segment monitoring software is vastly underutilized due to false positive alarms, with resultant alarm fatigue. Current ST algorithms may contribute to alarm fatigue because; (1) they are not designed with a delay (minutes), rather alarm to brief spikes (i.e., turning, heart rate changes), and (2) alarm to changes in a single ECG lead, rather than contiguous leads. PURPOSE: This study was designed to determine sensitivity, and specificity, of ST algorithms when accounting for; ST magnitude (100µV vs 200µV), duration, and changes in contiguous ECG leads (i.e., aVL, I, - aVR, II, aVF, III; V1, V2, V3, V4, V5, V6, V6, I). METHODS: This was a secondary analysis from the COMPARE Study, which assessed occurrence rates for transient myocardial ischemia in hospitalized patients with suspected ACS using 12-lead Holter. Transient myocardial ischemia was identified from Holter using >100µV ST-segment ↑ or ↓, in >1 ECG lead, >1min. Algorithms tested against Holter transient myocardial ischemia were done using the University of California San Francisco (UCSF) ECG algorithm and included: (1)100µV vs 200µV any lead during a 5-min ST average; (2)100µV vs 200µV any lead >5min, (3) 100µV vs 200µV any lead during a 5-min ST average in contiguous leads, and (4) 100µV vs 200µV>5min in contiguous leads (Table below). RESULTS: In 361 patients; mean age 63+12years, 63% male, 56% prior CAD, 43 (11%) had transient myocardial ischemia. Of the 43 patients with transient myocardial ischemia, 17 (40%) had ST-segment elevation events, and 26 (60%) ST-segment depression events. A higher proportion of patients with ST segment depression has missed ischemic events. Table shows sensitivity and specificity for the four algorithms tested. CONCLUSIONS: Sensitivity was highly variable, due to the ST threshold selected, with the 100µV measurement point being superior to the 200µV amplitude threshold. Of all the algorithms tested, there was moderate sensitivity and specificity (70% and 68%) using the 100µV ST-segment threshold, integrated ST-segment changes in contiguous leads during a 5-min average.

Technologic Distractions (Part 1): Summary of Approaches to Manage Alert Quantity With Intent to Reduce Alert Fatigue and Suggestions for Alert Fatigue Metrics.

OBJECTIVE: To provide ICU clinicians with evidence-based guidance on tested interventions that reduce or prevent alert fatigue within clinical decision support systems. DESIGN: Systematic review of PubMed, Embase, SCOPUS, and CINAHL for relevant literature from 1966 to February 2017. PATIENTS: Focus on critically ill patients and included evaluations in other patient care settings, as well. INTERVENTIONS: Identified interventions designed to reduce or prevent alert fatigue within clinical decision support systems. MEASUREMENTS AND MAIN RESULTS: Study selection was based on one primary key question to identify effective interventions that attempted to reduce alert fatigue and three secondary key questions that covered the negative effects of alert fatigue, potential unintended consequences of efforts to reduce alert fatigue, and ideal alert quantity. Data were abstracted by two reviewers independently using a standardized abstraction tool. Surveys, meeting abstracts, "gray" literature, studies not available in English, and studies with non-original data were excluded. For the primary key question, articles were excluded if they did not provide a comparator as key question 1 was designed as a problem, intervention, comparison, and outcome question. We anticipated that reduction in alert fatigue, including the concept of desensitization may not be directly measured and thus considered interventions that reduced alert quantity as a surrogate marker for alert fatigue. Twenty-six articles met the inclusion criteria. CONCLUSION: Approaches for managing alert fatigue in the ICU are provided as a result of reviewing tested interventions that reduced alert quantity with the anticipated effect of reducing fatigue. Suggested alert management strategies include prioritizing alerts, developing sophisticated alerts, customizing commercially available alerts, and including end user opinion in alert selection. Alert fatigue itself is studied less frequently, as an outcome, and there is a need for more precise evaluation. Standardized metrics for alert fatigue is needed to advance the field. Suggestions for standardized metrics are provided in this document.

ECG-derived Cheyne-Stokes respiration and periodic breathing in healthy and hospitalized populations.

BACKGROUND: Cheyne-Stokes respiration (CSR) has been investigated primarily in outpatients with heart failure. In this study we compare CSR and periodic breathing (PB) between healthy and cardiac groups. METHODS: We compared CSR and PB, measured during 24 hr of continuous 12-lead electrocardiographic (ECG) Holter recording, in a group of 90 hospitalized patients presenting to the emergency department with symptoms suggestive of acute coronary syndrome (ACS) to a group of 100 healthy ambulatory participants. We also examined CSR and PB in the 90 patients presenting with ACS symptoms, divided into a group of 39 (43%) with confirmed ACS, and 51 (57%) with a cardiac diagnosis but non-ACS. SuperECG software was used to derive respiration and then calculate CSR and PB episodes from the ECG Holter data. Regression analyses were used to analyze the data. We hypothesized SuperECG software would differentiate between the groups by detecting less CSR and PB in the healthy group than the group of patients presenting to the emergency department with ACS symptoms. RESULTS: Hospitalized patients with suspected ACS had 7.3 times more CSR episodes and 1.6 times more PB episodes than healthy ambulatory participants. Patients with confirmed ACS had 6.0 times more CSR episodes and 1.3 times more PB episodes than cardiac non-ACS patients. CONCLUSION: Continuous 12-lead ECG derived CSR and PB appear to differentiate between healthy participants and hospitalized patients.

Cardiovascular responses to energy drinks in a healthy population: The C-energy study.

BACKGROUND: Energy drink consumption has increased significantly over the past decade and is associated with greater than 20,000 emergency department visits per year. Most often these visits are due to cardiovascular complaints ranging from palpitations to cardiac arrest. OBJECTIVE: To determine if energy drinks alter; blood pressure, electrolytes, activated bleeding time (ACT), and/or cardiac responses measured with a 12-lead electrocardiographic (ECG) Holter. METHODS: Continuous ECG data was collected for five hours (30 minutes baseline and 4 hours post consumption [PC]). Subjects consumed 32 ounces of energy drink within one hour and data (vital signs and blood samples) was collected throughout the study period. Paired students t-test and a corresponding non-parametric test (Wilcoxon signed rank) were used for analysis of the data. RESULTS: Fourteen healthy young subjects were recruited (mean age 28.6 years). Systolic blood pressure (baseline=132, ±7.83; PC=151, ±11.21; P=.001); QTc interval (baseline=423, ±22.74; PC=503, ±24.56; P<.001); magnesium level (baseline 2.04, ± 0.09; PC=2.13, ±0.15; P=.05); and calcium level (baseline=9.31, ±.28; PC=9.52, ±.22; P=.018) significantly increased from baseline. While potassium and ACT fluctuated (some subjects increased their levels while others decreased) these changes were not significant. Eight of the fourteen subjects (57%) developed a QTc >500 milliseconds PC. Other T-wave changes were noted in 9/14 (64.3%) subjects PC. CONCLUSIONS: Energy drinks increased systolic blood pressure, altered electrolytes, and resulted in repolarization abnormalities. These physiological responses can lead to arrhythmias and other abnormal cardiac responses highlighting the importance that emergency room personnel assess for energy drink consumption and potential toxicity.

Electrocardiographic indicators of acute coronary syndrome are more common in patients with ambulance transport compared to those who self-transport to the emergency department journal of electrocardiology.

INTRODUCTION: The American Heart Association recommends individuals with symptoms suggestive of acute coronary syndrome (ACS) activate the Emergency Medical Services' (EMS) 911 system for ambulance transport to the emergency department (ED), which enables treatment to begin prior to hospital arrival. Despite this recommendation, the majority of patients with symptoms suspicious of ACS continue to self-transport to the ED. The IMMEDIATE AIM study was a prospective study that enrolled individuals who presented to the ED with ischemic symptoms. OBJECTIVES: The purpose of this secondary analysis was to determine differences in patients presenting the ED for possible ACS who arrive by ambulance versus self-transport on: 1) time-to-initial hospital electrocardiogram (ECG), 2) presence of ischemic ECG changes, and 3) patient characteristics. METHODS: Initial 12-lead ECGs acquired upon patient arrival to the ED were evaluated for ST-elevation, ST-depression, and T-wave inversion. ECG signs of ischemia were analyzed both individually and collapsed into an independent dichotomous variable (ED ECG ischemia yes/no) for statistical analysis. Patient characteristics tested included: gender, age, race, ethnicity, English speaking, living alone, mode of transport, and presenting symptoms (chest pain, jaw pain, shortness of breath, nausea/vomiting, syncope, and clinical history). RESULTS: In 1299 patients (mean age 63.9, 46.7% male), 384 (29.6%) patients arrived by ambulance to the ED. The mean time-to-initial ECG was 47minutes for ambulance patients versus 53minutes for self-transport patients (p<0.001). Mode of transport was found to be an independent predictor for time-to-initial ECG controlling for age, gender, and race (p=0.004). There were significantly higher rates of ECG changes of ischemia for patients who arrived by ambulance versus self-transport (p=0.02), and patient characteristics differed by mode of transport to the ED. DISCUSSION: Our findings indicate that less than 30% of individuals with symptoms of ACS activate the EMS '911' system for ambulance transport to the ED. Individuals more likely to activate 911 have timelier ECG but higher rates of ischemic changes, specifically ST-depression and T-wave inversion. Individuals least likely to activate 911 are women, younger individuals, Latino ethnicity, live with a significant other, and those experiencing chest or jaw pain.

Unplanned transfer from the telemetry unit to the intensive care unit in hospitalized patients with suspected acute coronary syndrome.

BACKGROUND: Most patients presenting with suspected acute coronary syndrome (ACS) are admitted to telemetry units. While telemetry is an appropriate level of care, acute complications requiring a higher level of care in the intensive care unit (ICU) occur. PURPOSE: Among patients admitted to telemetry for suspected ACS, we determine the frequency of unplanned ICU transfer, and examine whether ECG changes indicative of myocardial ischemia, and/or symptoms preceded unplanned transfer. METHOD: This was a secondary analysis from a study assessing occurrence rates for transient myocardial ischemia (TMI) using a 12-lead Holter. Clinicians were blinded to Holter data as it was used in the context research; off-line analysis was performed post discharge. Hospital telemetry monitoring was maintained as per hospital protocol. TMI was defined as >1mm ST-segment ↑ or ↓, in >1 ECG lead, >1minute. Symptoms were assessed by chart review. RESULTS: In 409 patients (64±13years), most were men (60%), Caucasian (93%), and had a history of coronary artery disease (47%). Unplanned transfer to the ICU occurred in 9 (2.2%), was equivalent by gender, and age (no transfer 64±13years vs transfer 67±11years). Four patients were transferred following unsuccessful percutaneous coronary intervention (PCI) attempt, four due to recurrent angina, and one due to renal and hepatic failure. Mean time from admission to transfer was 13±6hours, mean time to ECG detected ischemia was 6±5hours, and 8.8±5hours for symptoms prompting transfer. In two patients ECG detected ischemia and acute symptoms prompting transfer were simultaneous. In five patients, ECG detected ischemia was clinically silent. All patients eventually had symptoms that prompted transfer to the ICU. In all nine patients, there was no documentation or nursing notes regarding bedside ECG monitor changes prior to unplanned transfer. Hospital length of stay was longer in the unplanned transfer group (2days ± 2 versus 6days ± 4; p=0.018). CONCLUSIONS: In patients with suspected ACS, while unplanned transfer from telemetry to ICU is uncommon, it is associated with prolonged hospitalization. Two primary scenarios were identified; (1) following unsuccessful PCI, and (2) recurrent angina. Symptoms prompting unplanned transfer occurred, but happened on average 8.8 hours after hospital admission; whereas ECG detected ischemia preceding unplanned transfer occurred on average 6 hours after hospital admission.

Among Unstable Angina and Non-ST-Elevation Myocardial Infarction Patients, Transient Myocardial Ischemia and Early Invasive Treatment Are Predictors of Major In-hospital Complications.

BACKGROUND: Treatment for unstable angina (UA) or non-ST-elevation myocardial infarction (NSTEMI) is aimed at plaque stabilization to prevent infarction. Two treatment strategies are (1) invasive (ie, cardiac catheterization laboratory <24 hours after admission) or (2) selectively invasive (ie, medications with cardiac catheterization laboratory >24 hours for recurrent symptoms). However, it is not known if the frequency of transient myocardial ischemia (TMI) or complications during hospitalization varies by treatment. PURPOSE: We aimed to (1) examine occurrence of TMI in UA/NSTEMI, (2) compare frequency of TMI by treatment pathway, and (3) determine predictors of in-hospital complications (ie, death, myocardial infarction [MI], pulmonary edema, shock, dysrhythmia with intervention). METHODS: Hospitalized patients with coronary artery disease (ie, history of MI, percutaneous coronary intervention/stent, coronary artery bypass graft, >50% lesion via angiogram, or positive troponin) were recruited, and 12-lead electrocardiogram Holter initiated. Clinicians, blinded to Holter data, decided treatment strategy; offline analysis was done after discharge. Transient myocardial ischemia was defined as more than 1-mm ST segment ↑ or ↓, in more than 1 electrocardiographic lead, more than 1 minute. RESULTS: Of 291 patients, 91% were white, 66% were male, 44% had prior MI, and 59% had prior percutaneous coronary intervention/stent or coronary artery bypass graft. Treatment pathway was early in 123 (42%) and selective in 168 (58%). Forty-nine (17%) had TMI: 19 (15%) early invasive, 30 (18%) selective (P = .637). Acute MI after admission was higher in patients with TMI regardless of treatment strategy (early: no TMI 4% vs yes TMI 21%; P = .020; selective: no TMI 1% vs yes TMI 13%; P = .0004). Predictors of major in-hospital complication were TMI (odds ratio, 9.9; 95% confidence interval, 3.84-25.78) and early invasive treatment (odds ratio 3.5; 95% confidence interval, 1.23-10.20). CONCLUSIONS: In UA/NSTEMI patients treated with contemporary therapies, TMI is not uncommon. The presence of TMI and early invasive treatment are predictors of major in-hospital complications.

Evidence-Based Heart Failure Medications and Cognition.

BACKGROUND: The etiology of cognitive impairment in heart failure (HF) is controversial and likely multifactorial. Physicians may hesitate to prescribe evidence-based HF medication because of concerns related to potential negative changes in cognition among a population that is already frequently impaired. We conducted a study to determine if prescription of evidence-based HF medications (specifically, ß-blockers, angiotensin-converting enzyme inhibitors, angiotensin-receptor blocking agents, diuretics, and aldosterone inhibitors) was associated with cognition in a large HF sample. METHODS: A total of 612 patients completed baseline data collection for the Rural Education to Improve Outcomes in Heart Failure clinical trial, including information about medications. Global cognition was evaluated using the Mini-Cog. RESULTS: The sample mean (SD) age was 66 (13) years, 58% were men, and 89% were white. Global cognitive impairment was identified in 206 (34%) of the 612 patients. Prescription of evidence-based HF medications was not related to global cognitive impairment in this sample. This relationship was maintained even after adjusting for potential confounders (eg, age, education, and comorbid burden). CONCLUSION: Prescription of evidence-based HF medications is not related to low scores on a measure of global cognitive function in rural patients with HF.

Research: Association of Low-Amplitude QRSs with False-Positive Asystole Alarms.

BACKGROUND: Although electrocardiographic monitoring is valuable for continuous surveillance of intensive care unit (ICU) patients, false alarms are common and have been cited as a cause of alarm fatigue. ANSI/AAMI EC12:2002 states that electrocardiograms (ECGs) should not detect a QRS if the waveform is less than 0.15 mV (1.5 mm) for adult patients, in order to avoid mislabeling P waves or baseline noise as QRSs during complete heart block or asystole. However, ECG software algorithms often use more conservative QRS thresholds, which may result in false-positive asystole alarms in patients with low-amplitude QRS complexes. OBJECTIVES: To 1) assess the frequency of low QRS amplitude in a group of ICU patients with one or more false-positive asystole alarms and 2) determine whether low-amplitude QRSs are associated with false-positive asystole alarms during continuous ECG monitoring. METHODS: Hospital-acquired standard 12-lead ECGs were examined in a group of 82 ICU patients who had one or more false-positive asystole alarms. Low QRS amplitude was defined as a unidirectional (only positive or negative) QRS of less than 5 mm in two of four leads (I, II, III, and V1). RESULTS: Low-amplitude QRSs were present in 45 of 82 (55%) patients. The presence of low-amplitude QRSs did not differ according to age, sex, or race. Patients treated in the cardiac ICU had the highest proportion of low-amplitude QRSs. An equivalent proportion of patients had false-positive asystole alarms by group (no low-amplitude QRSs 95% vs. low-amplitude QRSs 87%; P = 0.229). Eight patients (10%) had both true- and false-positive asystole alarms (two [5%] with no low-amplitude QRSs and six [13%] with low-amplitude QRSs; P = 0.229). CONCLUSION: Low-amplitude QRS, as assessed from hospital 12-lead ECGs, occurs frequently and is more common in cardiac ICU patients. However, this ECG feature did not identify patients with false-positive asystole alarms during continuous ECG monitoring.